基于自适应遗传算法的异步电机矢量控制参数优化与仿真  

Optimization and simulation of asynchronous motor vector control parameter based on adapted genetic algorithm

作　　者：冯杏辉[1] 方建安[1] 许红磊[1] 吴瑞岩[1] 

机构地区：[1]东华大学信息科学与技术学院,上海201620

出　　处：《机电工程》2010年第11期103-105,共3页Journal of Mechanical & Electrical Engineering

摘　　要：自动控制领域中PID参数的整定是一个极其重要的问题。为解决工程人员凭经验对异步电机控制器参数整定难寻到最优解的问题,将速度误差积分型作为目标函数,采用惩罚措施,利用自适应遗传算法对异步电机速度控制器的参数进行优化、仿真,并与利用常规PID参数整定获得的速度曲线相对比,实验结果表明,用自适应遗传算法优化的参数,可以提高系统的控制精度、动态性能。PID parameters tuning is an extremely important issue in the control field.Accoding to the engineer＇s experience,it is always very hard to find the optimal solution of asynchronous machine speed controller＇s parameter.In order to solve the problem,punitive measures and adapted genetic algorithm were applied to optimize the asynchronous machine speed controller＇s parameter and then it was slinulated using rate error integral as the objective function.By comparing with the speed curve that use conventional PID parameter,the experimental results show that the optimized parameters can improve the control precision and dynamic performance.

关 键 词：异步电动机 矢量控制 自适应遗传算法 

分 类 号：TM343[电气工程—电机] TP273.2[自动化与计算机技术—检测技术与自动化装置]